Relatively large and sophisticated web sites typically implement some form of personalization system to provide personalized content, such as personalized item recommendations, to their users. The personalization system typically monitors and records one or more types of item-related user activity such as item purchases, item viewing events, and/or item rentals, and analyzes the collected data to detect and quantify associations between particular items. When a user accesses a particular item, such as a particular product in a catalog of an e-commerce site, or an article on a news site, an appropriate message may be displayed notifying the user of related items (e.g., “people who bought this item also bought . . . ,” or “people who viewed this item also viewed . . . ”). The personalization system may also generate personalized item recommendations that are based on a target user's purchase history, item viewing history, item ratings, and/or some other type of user data.
Unfortunately, personalization systems tend to be expensive to implement and maintain. For example, a relatively sophisticated personalization system typically requires infrastructure components which, among other tasks, store customer behavior data, process the stored behavior data to detect the item associations, and store databases which relate items to one another. As a result, among other reasons, sophisticated personalization systems are typically available only to relatively large companies.